A content (software) distribution method is known in which, for example, an acoustic signal or the like is encrypted and then broadcast or recorded to a recording medium so that only a person who purchased a key for decryption is permitted to listen to the signal.
As an encryption method, for example, a method is known in which an initial value of a random-number sequence is given as a key signal for a bit string of a PCM acoustic signal and then a bit string obtained by taking an exclusive OR between the generated random-number sequence of 0/1 and the PCM bit string is transmitted or recorded to a recording medium. As this method is used, a person who acquired the key signal can correctly reproduce the acoustic signal and a person who did not acquire the key signal can only reproduce noise. Of course, it is also possible to use a more complicated method such as so-called DES (Data Encryption Standard) as an encryption method. Description of the DES standard is disclosed in “Federal Information Processing Standards Publication 46, Specifications for the DATA ENCRYPTION STANDARD, Jan. 15, 1977.”
On the other hand, a method for compressing an acoustic signal and then broadcasting or recording the compressed acoustic signal to a recording medium is popularized, and recording media which enable recording of a coded audio signal or the like, such as a magneto-optical disc, are broadly used.
There are various techniques for high-efficiency coding of an audio signal, voice signal or the like. For example, such techniques may include subband coding (SBC), which is a non-blocked frequency band division system for dividing an audio signal or the like on the time axis into a plurality of frequency bands without blocking and then coding the band-divided audio signal, and so-called transform coding, which is a blocked frequency band division system for transforming (spectrally transforming) a signal on the time axis to a signal of the frequency axis, then dividing the signal into a plurality of frequency bands and coding the signal of each band. Moreover, a high-efficiency coding technique combining the above-described subband coding with transform coding is considered. In that case, for example, after frequency band division is carried out by the above-described subband coding, the signal of each band is spectrally transformed to a signal on the frequency axis and the spectrally transformed signal of each band is coded.
As a filter for the above-described technique, for example, a QMF filter is used. The QMF filter is described in “R. E. Crochiere, Digital coding of speech in subbands, Bell Syst. Tech. J. Vol.55, No.8, 1976”. Moreover, a filter division technique with equal bandwidth is disclosed in “Joseph H. Rothweiler, Polyphase Quadrature Filters—A new subband coding technique, ICASSP 83, BOSTON”.
As the above-described spectral transform, for example, the time axis is transformed to the frequency axis by blocking an input audio signal by predetermined unit time (frame) and then performing discrete Fourier transform (DFT), discrete cosine transform (DCT), modified discrete cosine transform (MDCT) or the like on each of the blocks. MDCT is described in “J.P. Princen, A. B. Bradley, Univ. of Surrey Royal Melbourne Inst. of Tech., Subband/Transform Coding Using Filter Band Designs Based on Time Domain Aliasing Cancellation, ICASSP, 1987”.
If the above-described DFT or DCT is used as a method for transforming a waveform signal to the spectrum, M independent real-number data are provided by performing transform on a time block consisting of M samples. To reduce the connection distortion between time blocks, each time block is usually overlapped with both adjacent blocks by M1 samples each. Therefore, on average, M real-number data are quantized and coded for (M–M1) samples in DFT or DCT.
On the other hand, if the above-described MDCT is used as a method for transforming a waveform signal to the spectrum, M independent real-number data are provided from 2M samples as a result of overlapping both adjacent time blocks by M samples each. Therefore, on average, M real-number data are quantized and coded for M samples in MDCT. A decoding device can reconstruct the waveform signal by performing inverse transform on each block of the code obtained by using MDCT and then adding the resulting waveform elements while letting them interfere with each other.
Generally, by elongating a time block for transform, the frequency resolution of the spectrum is enhanced and the energy concentrates at a specific spectral component. Therefore, by using MDCT in which each block is overlapped with both adjacent blocks by half each to perform transform with a longer block length and in which the number of resulting spectral signals is not increased from the number of the original time samples, more efficient coding can be carried out than when DFT or DCT is used. Moreover, by having each block have a sufficient long overlap with the adjacent blocks, the distortion between the blocks of the waveform signal can be reduced.
By quantizing the signal thus divided to each band by the filter or spectral transform, a band where quantization noise is generated can be controlled and more auditorily efficient coding can be performed by utilizing characteristics such as masking effect. By carrying out normalization for each band with the maximum value of absolute values of signal components in the band before performing quantization, more efficient coding can be performed.
The frequency division width in the case of quantizing each frequency component obtained by frequency band division is determined, for example, in consideration of the human auditory characteristic. Specifically, an audio signal may be divided into a plurality of bands (for example 25 bands) with broader bandwidths for higher-frequency bands which are generally called critical bands. When coding data of each band in this case, coding is carried out by using predetermined bit distribution to each band or adaptive bit allocation to each band. For example, when coding coefficient/factor data resulting from the above-described MDCT processing by the above-described bit allocation, the MDCT coefficient/factor data of each band resulting from MDCT of each of the blocks is coded by using an adaptive number of allocated bits.
For such bit allocation, the following two techniques are known. Specifically, “R. Zelinski and P. Noll, Adaptive Transform Coding of Speech Signals, IEEE Transactions of Acoustics, Speech, and Signal Processing, vol. ASSP-25, No.2, Aug. 1977”, discloses bit allocation based on the magnitude of a signal of each band. In this system, though the quantization noise spectrum is flat and the noise energy is minimum, the actual perception of noise is not optimum because the auditory masking effect is not utilized. “M. A. Kransner, MIT, The critical band coder—digital encoding of the perceptual requirements of the auditory system, ICASSP 1980”, discloses a technique in which a necessary signal-to-noise ratio for each band is obtained using auditory masking, thus performing fixed bit allocation. With this technique, however, even when measuring characteristics by using a sine wave input, a satisfactory characteristic value is not obtained because of fixed bit allocation.
To solve these problems, a high-efficiency coding device is proposed in which all the bits that can be used for bit allocation are divisionally used for a fixed bit allocation pattern predetermined for each small block and for bit allocation dependent on the magnitude of the signal of each block and in which the division ratio depends on a signal related to the input signal so that the proportion of division to the fixed bit allocation pattern is increased for a smoother spectrum of the signal.
According to this technique, if the energy concentrates at a specific spectrum, as in a sine wave input, the signal-to-noise ratio can be significantly improved as a whole by allocating many bits to a block containing that spectrum. Generally, since the human auditory sense is very sensitive to a signal having an acute spectral component, the improvement in the signal-to-noise ratio by using this technique is effective not only for improvement in the numerical value in measurement but also for improvement in the sound quality perceived by the auditory sense.
Many other techniques for bit allocation are proposed. As the auditory model is elaborated further and the coding device has a sufficient capability, more auditorily efficient coding is made possible. In these techniques, typically, a bit allocation reference value of a real number which realizes the signal-to-noise characteristic found by calculation with high fidelity is found, and an integer which approximates the reference value is used as the number of allocated bits.
In the specification and drawings of the Japanese Patent Application No. H5-152865 or WO94/28633 proposed by the present inventors, a method is proposed in which a tonal component that is particularly important in terms of the auditory sense, that is, a signal component with energy concentrated around a specific frequency, is separated from a spectral signal and coded separately from the other spectral components. This enables efficient coding of an audio signal etc. at a high compression rate while causing little auditory deterioration.
To construct an actual code string, first, quantization accuracy information and normalization factor (coefficient) information may be coded using a predetermined number of bits for each band on which normalization and quantization are performed, and then a normalized and quantized spectral signal may be coded. Moreover, the ISO/IEC 11172-3:1993(E), 1993 describes a high-efficiency coding system in which the number of bits representing quantization accuracy information is set to vary depending on the band. It is standardized that the number of bits representing quantization accuracy information is decreased toward higher frequency bands.
Instead of directly coding quantization accuracy information, a method is known in which quantization accuracy information is decided from normalization factor information in a decoding device. In this method, however, the relation between normalization factor information and quantization accuracy information is decided when the standard is set. Therefore, control of the quantization accuracy based on a more advanced auditory model cannot be introduced in the future. Moreover, if the compression rate to be realized is variable, the relation between normalization factor information and quantization accuracy information must be defined for each compression rate.
There is also known a method for more efficient coding by coding a quantized spectral signal using a variable-length code described in “D. A. Huffman, A Method for Construction of Minimum Redundancy Codes, Proc. I.R.E., 40, p.1098 (1952)”.
Meanwhile, a software distribution method is known in which an acoustic signal or the like coded by the above-described methods is encrypted and broadcast or recorded to a recording medium so that only a person who purchased a key is permitted to listen to the signal. As an encryption method, for example, a method is known in which an initial value of a random-number sequence is given as a key signal for a bit string of a PCM (pulse code modulation) acoustic signal or a coded signal and then a bit string obtained by taking an exclusive OR between the generated random-number sequence of 0/1 and the bit string is transmitted or recorded to a recording medium. As this method is used, only a person who acquired the key signal can correctly reproduce the acoustic signal and a person who did not acquire the key signal can only reproduce noise. Of course, it is also possible to use a more complicated method as an encryption method.
However, in these scrambling methods, if there is no key or if software is reproduced by ordinary reproducing means, what is reproduced is noise and the content of the software cannot be grasped. Therefore, these method cannot be used for applications such as distributing a disc having music recorded thereon with relatively low sound quality and allowing a person who listens to the music on trial to purchase only a key for a tune which the person likes and to reproduce the tune with high sound quality, or allowing a person to listen the software on trial and then to newly purchase a disc on which the software is recorded with high sound quality.
Conventionally, in the case of encrypting a high-efficiency coded signal, it is difficult to prevent the compression efficiency from lowering while providing a code string which is significant to ordinary reproducing means. Specifically, in the case where a code string obtained by high-efficiency coding is scrambled as described above, only noise is generated by reproducing the code string. Moreover, if the scrambled code string is not conformable to the original high-efficiency coding standard, the reproducing means might not operate at all. On the other hand, if the quantity of information is reduced, for example, by utilizing the auditory characteristics in the case where a PCM signal is scrambled and then high-efficiency coded, the signal obtained by scrambling the PCM signal cannot necessarily reproduced when the high-efficiency coding is canceled. Therefore, it is difficult to correctly descramble the signal. For this reason, a method which enables correct descrambling must be selected at the sacrifice of the efficiency in the compression method.
Thus, the Japanese Publication of Unexamined Patent Application No. H10-135944 proposed by the present inventors discloses an audio coding system which enables trial listening without a key with respect to a narrow-band signal produced by encrypting only a high-frequency side of a spectral signal which is transformed from a music signal and then coded. Specifically, in this system, the high-frequency side is encrypted and bit allocation information on the high-frequency side is replaced by dummy data so that the true bit allocation information on the high-frequency side is recorded at a position which is neglected by an ordinary decoder. By employing this system, for example, it is possible to enjoy listening to only one's favorite music with high sound quality as a result of trial listening.
In the technique described in the above-described Japanese Publication of Unexamined Patent Application No. H10-135944, the security depends only on the encryption. Therefore, if the signal is decrypted, there is a possibility that the music of high sound quality can be listened to without charging any fee for it.
In the case of low quality (sound quality or image quality) of trial viewing/listening, what quality of signal can be enjoyed after the purchase is unknown and whether to purchase or not is difficult to decide. However, if trial viewing/listening with relatively high quality is made possible, many users may think they can enjoy the content well without purchasing it.